With the growing popularity of shared resources, large volumes of complex data of different
types are collected automatically. Traditional data mining algorithms generally have …

Nonoverlapping sequential pattern mining (SPM) is a data analysis task, which aims at
identifying repetitive sequential patterns with gap constraint in a set of discrete sequences …

Pattern mining has been an attractive topic for many researchers since its first introduction.
Clickstream mining, a specific version of sequential pattern mining, has been shown to be …

Mining sequential patterns is used to discover all the frequent sequences in a sequence
database. However, the mining may return a huge number of patterns, while the users are …

Sequential pattern mining is an important task in data mining. Its subproblem, clickstream
pattern mining, is starting to attract more research due to the growth of the Internet and the …

We consider the problem of mining web access patterns with super-pattern constraint. This
constraint requires that the sequential patterns in the sequence database must contain a …

The problem of mining frequent sequential patterns (FSPs) has attracted a great deal of
research attention. Although there are many efficient algorithms for mining FSPs, the mining …

Mining sequential rules from a sequence database usually returns a set of rules with great
cardinality. However, in real world applications, the end-users are often interested in a …

Data mining has become increasingly important in the Internet era. The problem of mining
inter-sequence pattern is a sub-task in data mining with several algorithms in the recent …

Mining frequent closed sequential pattern (FCSPs) has attracted a great deal of research
attention, because it is an important task in sequences mining. In recently, many studies …